In this file, the goal is to:
Figure 1. The full domain (light grey), available study sites (dark grey), and focal study sites (red).
Focal study sites have been selected on the basis of the following criteria:
To better stratify our sampling, we’ll use k-means clustering to divide up the cells within the domain into clusters.
The variables going into the clustering are:
Here I’m using k-means clustering to divide the data into 20 clusters. The number 20 was chosen entirely arbitrarily.
Figure 2. Spatial distribution of clusters. Polygons denote focal sampling locations.
Figure 3. Distribution of clusters across the domain (grey) and focal regions (blue).
Figure 4. Mean Annual Temperature vs. Mean Annual Precipitation. Colored dots represent clusters in the focal sites and grey areas represent the entire domain.
Figure 5. Precipitation Seasonality vs. Soil Depth. Colored dots represent clusters in the focal sites and grey areas represent the entire domain.
Figure 6. Distance to water vs. Drought. Colored dots represent clusters in the focal sites and grey areas represent the entire domain.
Figure 7. Distribution of biomes across the domain (grey) and focal regions (blue)
Include a leaflet plot here with focal sites broken into smaller polygons by cluster. Then color the polygons by cluster Intersect polygons with cluster polygons
Figure 8. Sampling options within parks. Park boundaries are denoted by black lines, sampling locations are colored by cluster.